---
title: NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit"
md_url: "https://www.modelscope.cn/models/mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit.md"
repository: mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit
last_updated: 2026-08-11
license: other
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - nemotron_h
architectures:
  - NemotronHForCausalLM
base_model:
  - nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
base_model_relation: quantized
parameters: 4.9B
tensor_type:
  - U32
  - F32
  - BF16
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - en
  - es
  - fr
  - de
  - it
  - ja
downloads: 52
stars: 0
tags:
  - nvidia
  - pytorch
  - nemotron-3.5
  - mlx
---

# NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit

> NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit - mlx-community 在 ModelScope 开源的模型。mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit

mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit 是 ModelScope 魔搭社区上的 4.9B 参数text-generation模型，采用 other 许可，基于 nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 构建。

- **Repository**: mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit
- **License**: other
- **Tasks**: text-generation
- **Parameters**: 4.9B
- **Base model**: nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
- **Tags**: nvidia, pytorch, nemotron-3.5, mlx
- **Downloads**: 52
- **Stars**: 0
- **Last updated**: 2026-08-11

Source: https://www.modelscope.cn/models/mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit

---

# mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit

This model [mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit](https://huggingface.co/mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit) was
converted to MLX format from
[nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16)
using mlx-lm version **0.31.3** (4-bit, group size 64).

NVIDIA-Nemotron-3.5-Lightning-30B-A3B is a hybrid Mamba-2 / attention
Mixture-of-Experts model (~31B total parameters, ~3B active per token).

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-4bit")

prompt = "Hello, who are you?"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```